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Abstract Determining Earth’s structure is paramount to unravel its interior dynamics. Seismic tomography reveals positive wave speed anomalies throughout the mantle that spatially correlate with the expected locations of subducted slabs. This correlation has been widely applied in plate reconstructions and geodynamic modelling. However, global travel-time tomography typically incorporates only a limited number of easily identifiable body wave phases and is therefore strongly dependent on the source-receiver geometry. Here, we show how global full-waveform inversion is less sensitive to source-receiver geometry and reveals numerous previously undetected positive wave speed anomalies in the lower mantle. Many of these previously undetected anomalies are situated below major oceans and continental interiors, with no geologic record of subduction, such as beneath the western Pacific Ocean. Moreover, we find no statistically significant correlation positive anomalies as imaged using full-waveform inversion and past subduction. These findings suggest more diverse origins for these anomalies in Earth’s lower mantle, unlocking full-waveform inversion as an indispensable tool for mantle exploration.

Having been a seemingly unreachable ideal for decades, 3-D full-waveform inversion applied to massive seismic datasets has become reality in recent years. Often achieving unprecedented resolution, it has provided new insight into the structure of the Earth, from the upper few metres of soil to the entire globe. Motivated by these successes, the technology is now being translated to medical ultrasound and non-destructive testing. Despite remarkable progress, the computational cost of full-waveform inversion continues to be a major concern. It limits the amount of data that can be exploited, and it largely inhibits quantitative and comprehensive uncertainty analyses. These notes complement a presentation on recent developments in full-waveform inversion that are intended to reduce computational cost and assimilate more data, thereby improving tomographic resolution. The suite of strategies includes flexible and user-friendly spectral-element simulations, the design of wavefield-adapted meshes that harness prior information on wavefield geometry, dynamic mini-batch optimisation that naturally takes advantage of data redundancies, and collaborative multi-scale updating to jointly constrain crustal and mantle structure.

Abstract Effective use of the wealth of information provided by Distributed Acoustic Sensing (DAS) for mass movement monitoring remains a challenge. We propose a semi‐supervised neural network tailored to screen DAS data related to a series of rock collapses leading to a major failure of approximately 1.2 million m3 on 15 June 2023 in Brienz, Eastern Switzerland. Besides DAS, the dataset from 16 May to 30 June 2023 includes Doppler radar data for partially ground‐truth labeling. The proposed algorithm is capable of distinguishing between rock‐slope failures and background noise, including road and train traffic, with a detection precision of over 95%. It identifies hundreds of precursory failures and shows sustained detection hours before and during the major collapse. Event size and signal‐to‐noise ratio (SNR) are the key performance dependencies. As a critical part of our algorithm operates unsupervised, we suggest that it is suitable for general monitoring of natural hazards.

We present a distributed acoustic sensing (DAS) experiment at Grímsvötn, Iceland. This is intended to investigate volcano-microseismicity at Grímsvötn specifically, and to assess the suitability of DAS as a subglacial volcano monitoring tool in general. In spring 2021, we trenched a 12 km long fiber-optic cable into the ice sheet around and within the caldera, followed by nearly one month of continuous recording. An image processing algorithm that exploits spatial coherence in DAS data detects on average ~100 events per day, almost 2 orders of magnitude more than in the regional earthquake catalog. A nonlinear Bayesian inversion reveals the presence of pronounced seismicity clusters, containing events with magnitudes between −3.4 and 1.7. Their close proximity to surface volcanic features suggests a geothermal origin. In addition to painting a fine-scale picture of seismic activity at Grímsvötn, this work confirms the potential of DAS in subglacial volcano monitoring.

Abstract We present a long-range fiber-optic environmental deformation sensor based on active phase noise cancellation (PNC) in metrological frequency dissemination. PNC sensing exploits recordings of a compensation frequency that is commonly discarded. Without the need for dedicated measurement devices, it operates synchronously with metrological services, suggesting that existing phase-stabilized metrological networks can be co-used effortlessly as environmental sensors. The compatibility of PNC sensing with inline amplification enables the interrogation of cables with lengths beyond 1000 km, making it a potential contributor to earthquake detection and early warning in the oceans. Using spectral-element wavefield simulations that accurately account for complex cable geometry, we compare observed and computed recordings of the compensation frequency for a magnitude 3.9 earthquake in south-eastern France and a 123 km fiber link between Bern and Basel, Switzerland. The match in both phase and amplitude indicates that PNC sensing can be used quantitatively, for example, in earthquake detection and characterization.

We present distributed fiber‐optic sensing data from an airplane landing near the EastGRIP ice core drilling site on the Northeast Greenland Ice Stream. The recordings of exceptional clarity contain at least 15 easily visible wave propagation modes corresponding to various Rayleigh, pseudoacoustic, and leaky waves. In the frequency range from 8 to 55 Hz, seven of the modes can be identified unambiguously. Based on an a priori firn and ice model that matches P‐wave dispersion and the fundamental Rayleigh mode, a Backus–Gilbert inversion yields an S‐wavespeed model with resolution lengths as low as a few meters and uncertainties in the range of only 10 m/s. An empirical scaling from S wavespeed to density leads to a depth estimate of the firn–ice transition between 65 and 71 m, in agreement with direct firn core measurements. This work underlines the potential of distributed fiber‐optic sensing combined with strong unconventional seismic sources in studies of firn and ice properties, which are critical ingredients of ice core climatology, as well as ice sheet dynamics and mass balance calculations.

Abstract The use of fiber infrastructures for environmental sensing is attracting global interest, as optical fibers emerge as low cost and easily accessible platforms exhibiting a large terrestrial deployment. Moreover, optical fiber networks offer the unique advantage of providing observations of submarine areas, where the sparse existence of permanent seismic instrumentation due to cost and difficulties in deployment limits the availability of high-resolution subsea information on natural hazards in both time and space. The use of optical techniques that leverage pre-existing fiber infrastructure can efficiently provide higher resolution coverage and pave the way for the identification of the detailed structure of the Earth especially on seismogenic submarine faults. The prevailing optical technique for use in earthquake detection and structural analysis is distributed acoustic sensing (DAS) which offers high spatial resolution and sensitivity, however is limited in range (

Entirely covered by the Vatnajökull ice cap, Grímsvötn is among Iceland’s largest and most hazardous volcanoes. Here we demonstrate that fiber-optic sensing technology deployed on a natural floating ice resonator can detect volcanic tremor at the level of few nanostrain/s, thereby enabling a new mode of subglacial volcano monitoring under harsh conditions. A 12.5 km long fiber-optic cable deployed on Grímsvötn in May 2021 revealed a high level of local earthquake activity, superimposed onto nearly monochromatic oscillations of the caldera. High data quality combined with dense spatial sampling identify these oscillations as flexural gravity wave resonance of the ice sheet that floats atop a subglacial lake. Although being affected by the ambient wavefield, the time–frequency characteristics of observed caldera resonance require the presence of an additional persistent driving force with temporal variations over several days, that is most plausibly explained in terms of low-frequency volcanic tremor. In addition to demonstrating the logistical feasibility of installing a large, high-quality fiber-optic sensing network in a subarctic environment, our experiment shows that ice sheet resonance may act as a natural amplifier of otherwise undetectable (volcanic) signals. This suggests that similar resonators might be used in a targeted fashion to improve monitoring of ice-covered volcanic systems.

Abstract Knowledge of lithospheric structure is essential for understanding the impact of continental collision and oceanic subduction on surface tectonic configurations. Full‐waveform tomographic images reveal lateral heterogeneities and anisotropy of the lithosphere and asthenosphere in Asia. Estimating lithospheric thickness from seismic velocity reductions at depth exhibits large variations underneath different tectonic units. The thickest cratonic roots are present beneath the Sichuan, Ordos, and Tarim basins and central India. Radial anisotropy signatures of 11 representative tectonic provinces uncover the different nature and geodynamic processes of their respective past and present deformation. The large‐scale continental lithospheric deformation is characterized by low‐velocity anomalies from the Himalayan Orogen to the Baikal rift zone in central Asia, coupled with the post‐collision thickening of the crust. The horizontal low‐velocity layer of ∼100–300 km depth extent below the lithosphere points toward the existence of the asthenosphere beneath East and Southeast Asia, with heterogeneous anisotropy indicative of channel flows.

As woody plants provide much of the trophic basis for food webs in forests their species richness, but also stand age and numerous further variables such as vegetation structure, soil properties and elevation can shape assemblages of ground beetles (Coleoptera: Carabidae). However, the combined impact of these numerous variables on ground beetle diversity and community structure has rarely been studied simultaneously. Therefore, ground beetles were studied in 27 plots in a highly diverse and structurally heterogeneous subtropical forest ecosystem, the Gutianshan National Park (southeast China) using pitfall traps and flight interception traps. Both trapping methods collected partly overlapping species spectra. The arboreal fauna was dominated by lebiines and to a smaller extent by tiger beetles and platynines; the epigeic fauna comprised mostly representatives of the genus Carabus and numerous tribes, especially anisodactylines, pterostichines, and sphodrines. Ground beetle species richness, abundance, and biomass of the pitfall trap catches were analyzed with generalized linear mixed models (GLMMs), fitted with seven environmental variables. Four of these variables influenced the ground beetle assemblages: Canopy cover, herb cover, pH-value of the topsoil and elevation. Contrary to our expectations, woody plant species richness and stand age did not significantly affect ground beetle assemblages. Thus, ground beetles seem to respond differently to environmental variables than ants and spiders, two other predominantly predatory arthropod groups that were studied on the same plots in our study area and which showed distinct relationships with woody plant richness. Our results highlight the need to study a wider range of taxa to achieve a better understanding of how environmental changes affect species assemblages and their functioning in forest ecosystems.

Abstract Background Species-specific genotypic features, local neighbourhood interactions and resource supply strongly influence the tree stature and growth rate. In mixed-species forests, diversity-mediated biomass allocation has been suggested to be a fundamental mechanism underlying the positive biodiversity-productivity relationships. Empirical evidence, however, is rare about the impact of local neighbourhood diversity on tree characteristics analysed at a very high level of detail. To address this issue we analysed these effects on the individual-tree crown architecture and tree productivity in a mature mixed forest in northern Germany. Methods Our analysis considers multiple target tree species across a local neighbourhood species richness gradient ranging from 1 to 4. We applied terrestrial laser scanning to quantify a large number of individual mature trees (N = 920) at very high accuracy. We evaluated two different neighbour inclusion approaches by analysing both a fixed radius selection procedure and a selection based on overlapping crowns. Results and conclusions We show that local neighbourhood species diversity significantly increases crown dimension and wood volume of target trees. Moreover, we found a size-dependency of diversity effects on tree productivity (basal area and wood volume increment) with positive effects for large-sized trees (diameter at breast height (DBH) > 40 cm) and negative effects for small-sized (DBH

Emerging high-performance computing systems, combined with increasingly detailed 3-D Earth models and physically consistent numerical wave propagation solvers, are opening up new opportunities for urgent seismic computing. This may help, for instance, to guide emergency response teams in the wake of large earthquakes. A key component of urgent seismic computing is the early availability of source mechanism estimates, well before conventional and time-consuming moment tensor inversions are carried out and published. Here, we introduce a methodology that rapidly estimates focal mechanisms (FM) for moderate and large earthquakes (Mw > 4.0) by means of statistical and clustering algorithms. The fundamental rationale behind the method is that events of a certain size tend to be similar to other events of similar size in similar locations. In this work, two different strategies are used to provide different FM solutions: the first is based only in spatial considerations including statistical analysis, and the other one is based on a data clustering algorithm. We exemplify our methodology with six different subsets of the open-access Global Centroid Moment Tensor (GCMT) catalog. Specifically, our study datasets include events from Japan, New Zealand, California, Mexico, Iceland, and Italy, which represent six seismically active regions, with a large FM variability. Our results show a 70–85% agreement between our fast FM estimates and inversion results, depending on the particular tectonic region, dataset size, and magnitude threshold. In addition, our FM estimation strategies only spend few seconds for processing, since they are totally independent of seismic record retrieval and inversion. Albeit not meant to be a substitute for CMT inversions, our methodologies can bridge the time gap between earthquake detection and FM inversion.

Here, Schuldt et al. collate data from two long-term grassland and forest biodiversity experiments to ask how plant diversity facets affect the diversity of higher trophic levels. The results show that positive effects of plant diversity on consumer diversity are mediated by plant structural and functional diversity, and vary across ecosystems and trophic levels.

Reforestation in sloping terrain is an important measure for soil erosion control and sustainable watershed management. The mechanical stability of such reforested stands, however, can be low due to a strong asymmetric shape of tree crowns. We investigated how neighbourhood tree species richness, neighbourhood pressure, tree height, and slope inclination affect crown asymmetry in a large-scale plantation biodiversity-ecosystem functioning experiment in subtropical China (BEF-China) over eight years. We took the advantage of terrestrial laser scanning (TLS) measurements, which provide non-destructive, high-resolution data of tree structure without altering tree interactions. Neighbourhood species richness significantly reduced crown asymmetry, and this effect became stronger at steeper slopes. Our results suggest that tree diversity promotes the mechanical stability of forest stands in sloping terrain and highlight the importance of TLS-data for a comprehensive understanding of the role of tree diversity in modulating crown interactions in mixed-species forest plantations.

Abstract In seismic tomography we map the wave speed structure inside the Earth, but we ultimately seek to interpret those images in terms of physical parameters. This is challenging because many parameters can trade‐off with each other to produce a given wave speed. The problem is compounded by the convention of mapping seismic structures as perturbations relative to a 1‐D reference model, rather than absolute wave speeds. Using a full waveform tomography model of Europe as a case study, we quantify the extent to which thermochemical and dynamic properties can be constrained using only S wave speed, expressed in absolute values. The wave speed distributions of this tomography model are compared with 4 million thermochemical models, whose seismic properties are computed via thermodynamic modeling. These models sample the full range of realistic mantle compositions, including variable water and melt contents, and mineral intrinsic anelasticity is taken into account. Intrinsic anelasticity causes waves to travel more slowly at higher temperatures, leading to seismic attenuation, but the sensitivity of the wave speed reduction to temperature is, in turn, controlled by the wave frequency. Global studies of surface waves indicate an anticorrelation between S wave speed and attenuation. We therefore only retain thermochemical models satisfying this anticorrelation. Our study indicates that the frequency dependence of anelasticity, α, depends on temperature or rheology, with α ≈ 0.1 being most appropriate in cold or lithospheric mantle and α ≈ 0.3 in warmer regions (i.e., the asthenosphere). Additionally, the slowest regions require specific compositions and/or a velocity‐weakening mechanism, such as partial melting, elastically accommodated grain boundary sliding, or water.

Though biodiversity is expected to be important in productivity in tree communities, there is little empirical evidence of this at local scales. Here, Fichtner et al. show that higher neighbourhood species richness increased tree growth, explaining over half of the variation in community productivity.

Abstract Herbivores and fungal pathogens are key drivers of plant community composition and functioning. The effects of herbivores and pathogens are mediated by the diversity and functional characteristics of their host plants. However, the combined effects of herbivory and pathogen damage, and their consequences for plant performance, have not yet been addressed in the context of biodiversity–ecosystem functioning research. We analyzed the relationships between herbivory, fungal pathogen damage and their effects on tree growth in a large‐scale forest‐biodiversity experiment. Moreover, we tested whether variation in leaf trait and climatic niche characteristics among tree species influenced these relationships. We found significant positive effects of herbivory on pathogen damage, and vice versa. These effects were attenuated by tree species richness—because herbivory increased and pathogen damage decreased with increasing richness—and were most pronounced for species with soft leaves and narrow climatic niches. However, herbivory and pathogens had contrasting, independent effects on tree growth, with pathogens decreasing and herbivory increasing growth. The positive herbivory effects indicate that trees might be able to (over‐)compensate for local damage at the level of the whole tree. Nevertheless, we found a dependence of these effects on richness, leaf traits and climatic niche characteristics of the tree species. This could mean that the ability for compensation is influenced by both biodiversity loss and tree species identity—including effects of larger‐scale climatic adaptations that have been rarely considered in this context. Our results suggest that herbivory and pathogens have additive but contrasting effects on tree growth. Considering effects of both herbivory and pathogens may thus help to better understand the net effects of damage on tree performance in communities differing in diversity. Moreover, our study shows how species richness and species characteristics (leaf traits and climatic niches) can modify tree growth responses to leaf damage under real‐world conditions.

Interest in measuring displacement gradients, such as rotation and strain, is growing in many areas of geophysical research. This results in an urgent demand for reliable and field-deployable instruments measuring these quantities. In order to further establish a high-quality standard for rotation and strain measurements in seismology, we organized a comparative sensor test experiment that took place in November 2019 at the Geophysical Observatory of the Ludwig-Maximilians University Munich in Fürstenfeldbruck, Germany. More than 24 different sensors, including three-component and single-component broadband rotational seismometers, six-component strong-motion sensors and Rotaphone systems, as well as the large ring laser gyroscopes ROMY and a Distributed Acoustic Sensing system, were involved in addition to 14 classical broadband seismometers and a 160 channel, 4.5 Hz geophone chain. The experiment consisted of two parts: during the first part, the sensors were co-located in a huddle test recording self-noise and signals from small, nearby explosions. In a second part, the sensors were distributed into the field in various array configurations recording seismic signals that were generated by small amounts of explosive and a Vibroseis truck. This paper presents details on the experimental setup and a first sensor performance comparison focusing on sensor self-noise, signal-to-noise ratios, and waveform similarities for the rotation rate sensors. Most of the sensors show a high level of coherency and waveform similarity within a narrow frequency range between 10 Hz and 20 Hz for recordings from a nearby explosion signal. Sensor as well as experiment design are critically accessed revealing the great need for reliable reference sensors.

The effects of atmospheric nitrogen (N) deposition on ecosystem functioning largely depend on the retention of N in different ecosystem compartments, but accumulation and partitioning processes have rarely been quantified in long-term field experiments. In the present study we analysed for the first time decadal-scale flows and allocation patterns of N in a heathland ecosystem that has been subject to airborne N inputs over decades. Using a long-term 15N tracer experiment, we quantified N retention and flows to and between ecosystem compartments (above-ground/below-ground vascular biomass, moss layer, soil horizons, leachate). After 9 years, about 60% of the added 15N-tracer remained in the N cycle of the ecosystem. The moss layer proved to be a crucial link between incoming N and its allocation to different ecosystem compartments (in terms of a short-term capture, but long-term release function). However, about 50% of the 15N captured and released by the moss layer was not compensated for by a corresponding increase in recovery rates in any other compartment, probably due to denitrification losses from the moss layer in the case of water saturation after rain events. The O-horizon proved to be the most important long-term sink for added 15N, as reflected by an increase in recovery rates from 18 to 40% within 8 years. Less than 2.1% of 15N were recovered in the podzol-B-horizon, suggesting that only negligible amounts of N were withdrawn from the N cycle of the ecosystem. Moreover, 15N recovery was low in the dwarf shrub above-ground biomass (

Understanding how trees respond to global change drivers is central to predict changes in forest structure and functions. Although there is evidence on the mode of nitrogen (N) and drought (D) effects on tree growth, our understanding of the interplay of these factors is still limited. Simultaneously, as mixtures are expected to be less sensitive to global change as compared to monocultures, we aimed to investigate the combined effects of N addition and D on the productivity of three tree species (Fagus sylvatica, Quercus petraea, Pseudotsuga menziesii) in relation to functional diverse species mixtures using data from a four-year field experiment in Northwest Germany. Here we show that species mixing can mitigate the negative effects of combined N fertilization and D events, but the community response is mainly driven by the combination of certain traits rather than the tree species richness of a community. For beech, we found that negative effects of D on growth rates were amplified by N fertilization (i.e. combined treatment effects were non-additive), while for oak and fir, the simultaneous effects of N and D were additive. Beech and oak were identified as most sensitive to combined N+D effects with a strong size-dependency observed for beech, suggesting that the negative impact of N+D becomes stronger with time as beech grows larger. As a consequence, the net biodiversity effect declined at the community level, which can be mainly assigned to a distinct loss of complementarity in beech-oak mixtures. This pattern, however, was not evident in the other species-mixtures, indicating that neighborhood composition (i.e. trait combination), but not tree species richness mediated the relationship between tree diversity and treatment effects on tree growth. Our findings point to the importance of the qualitative role (‘trait portfolio’) that biodiversity play in determining resistance of diverse tree communities to environmental changes. As such, they provide further understanding for adaptive management strategies in the context of global change.

The three-dimensional (3D) morphology of individual trees is critical for light interception, growth, stability and interactions with the local environment. Forest management intensity is a key driver of tree morphology, but how the long-term abandonment of silvicultural measures impacts trunk and crown morphological traits is not fully understood. Here, we take advantage of a long management intensity gradient combined with a high-resolution terrestrial laser scanning (TLS) approach to explore how management history affects the 3D structure of mature beech (Fagus sylvatica L.) trees. The management gradient ranged from long-term (>50 years) and short-term (>20 years) unmanaged to extensively and intensively managed beech stands. We determined 28 morphological traits and quantified the vertical distribution of wood volume along the trunk. We evaluated the differences in tree morphological traits between study stands using Tukey’s HSD test. Our results show that 93% of the investigated morphological traits differed significantly between the study stands. Significant differences, however, emerged most strongly in the stand where forest management had ceased >50 years ago. Furthermore, we found that the vertical distribution of trunk wood volume was highly responsive between stands with different management intensity, leading to a 67% higher taper top height and 30% lower taper of beech trees growing in long-term unmanaged stands compared to those in short-term unmanaged or managed stands. These results have important implications for management intensity decisions. It is suggested that the economic value of individual beech trees from long-term unmanaged forests can be expected to be very high. This might also translate to beech forests that are extensively managed, but we found that a few decades of implementation of such a silvicultural system is not sufficient to cause significant differences when compared to intensively managed stands. Furthermore, TLS-based high-resolution analyses of trunk and crown traits play a crucial role in the ability to better understand or predict tree growth responses to the current drivers of global change.

The role of competition in tree communities is increasingly well understood, while little is known about the patterns and mechanisms of the interplay between above- and belowground competition in tree communities. This knowledge, however, is crucial for a better understanding of community dynamics and developing adaptive near-natural management strategies. We assessed neighbourhood interactions in an unmanaged old-growth European beech (Fagus sylvatica) forest by quantifying variation in the intensity of above- (shading) and belowground competition (crowding) among dominant and co-dominant canopy beech trees during tree maturation. Shading had on average a much larger impact on radial growth than crowding and the sensitivity to changes in competitive conditions was lowest for crowding effects. We found that each mode of competition reduced the effect of the other. Increasing crowding reduced the negative effect of shading, and at high levels of shading, crowding actually had a facilitative effect and increased growth. Our study demonstrates that complementarity in above- and belowground processes enable F. sylvatica to alter resource acquisition strategies, thus optimising tree radial growth. As a result, competition seemed to become less important in stands with a high growing stock and tree communities with a long continuity of anthropogenic undisturbed population dynamics. We suggest that growth rates do not exclusively depend on the density of potential competitors at the intraspecific level, but on the conspecific aggregation of large-diameter trees and their functional role for regulating biotic filtering processes. This finding highlights the potential importance of the rarely examined relationship between the spatial aggregation pattern of large-diameter trees and the outcome of neighbourhood interactions, which may be central to community dynamics and the related forest ecosystem services.

Abstract: Climate and atmospheric changes affect forest ecosystems worldwide, but little is known about the interactive effects of global change drivers on tree growth. In the present study, we analyzed single and combined effects of nitrogen (N) fertilization and drought events (D) on the growth of European beech (Fagus sylvatica L.) saplings in a greenhouse experiment. We quantified morphological and physiological responses to treatments for one‐ and two‐year‐old plants. N fertilization increased the saplings’ aboveground biomass investments, making them more susceptible to D treatments. This was reflected by the highest tissue dieback in combined N and D treatments and a significant N × D interaction for leaf δ13C signatures. Thus, atmospheric N deposition can strengthen the drought sensitivity of beech saplings. One‐year‐old plants reacted more sensitively to D treatments than two‐year‐old plants (indicated by D‐induced shifts in leaf δ13C signatures of one‐year‐old and two‐year‐old plants by +0.5‰ and −0.2‰, respectively), attributable to their higher shoot:root‐ratios (1.8 and 1.2, respectively). In summary, the saplings’ treatment responses were determined by their phenotypic plasticity (shifts in shoot:root‐ratios), which in turn was a function of both the saplings’ age (effects of allometric growth trajectories = apparent plasticity) and environmental impacts (effects of N fertilization = plastic allometry).

There is ample evidence that continuously existing forests and afforestations on previously agricultural land differ with regard to ecosystem functions and services such as carbon sequestration, nutrient cycling and biodiversity. However, no studies have so far been conducted on possible long-term (>100 years) impacts on tree growth caused by differences in the ecological continuity of forest stands. In the present study we analysed the variation in tree-ring width of sessile oak (Quercus petraea (Matt.) Liebl.) trees (mean age 115-136 years) due to different land-use histories (continuously existing forests, afforestations both on arable land and on heathland). We also analysed the relation of growth patterns to soil nutrient stores and to climatic parameters (temperature, precipitation). Tree rings formed between 1896 and 2005 were widest in trees afforested on arable land. This can be attributed to higher nitrogen and phosphorous availability and indicates that former fertilisation may continue to affect the nutritional status of forest soils for more than one century after those activities have ceased. Moreover, these trees responded more strongly to environmental changes - as shown by a higher mean sensitivity of the tree-ring widths - than trees of continuously existing forests. However, the impact of climatic parameters on the variability in tree-ring width was generally small, but trees on former arable land showed the highest susceptibility to annually changing climatic conditions. We assume that incompletely developed humus horizons as well as differences in the edaphon are responsible for the more sensitive response of oak trees of recent forests (former arable land and former heathland) to variation in environmental conditions. We conclude that forests characterised by a long ecological continuity may be better adapted to global change than recent forest ecosystems.

Observations of glacier melt and runoff are of fundamental interest in the study of glaciers and their interactions with their environment. Considerable recent interest has developed around distributed acoustic sensing (DAS), a sensing technique which utilizes Rayleigh backscatter in fiber optic cables to measure the seismo-acoustic wavefield in high spatial and temporal resolution. Here, we present data from a month-long, 9 km DAS deployment extending through the ablation and accumulation zones on Rhonegletscher, Switzerland, during the 2020 melt season. While testing several types of machine learning (ML) models, we establish a regression problem, using the DAS data as the dependent variable, to infer the glacier discharge observed at a proglacial stream gauge. We also compare two predictive models that only depend on meteorological station data. We find that the seismo-acoustic wavefield recorded by DAS can be utilized to infer proglacial discharge. Models using DAS data outperform the two models trained on meteorological data with mean absolute errors of 0.64, 2.25 and 2.72 m3 s−1, respectively. This study demonstrates the ability of in situ glacier DAS to be used for quantifying proglacial discharge and points the way to a new approach to measuring glacier runoff.